fix: repoint chapter README Colab URLs at HowToGalaxy + align entries with actual tutorials

.url_check_allowlist.txt

@@ -9,36 +9,6 @@
 # Code of Conduct boilerplate
 http://geekfeminism.wikia.com/wiki/Conference_anti-harassment/Policy  # CODE_OF_CONDUCT.md:305
 
-# Colab refs to notebooks no longer in HowTo/workspace
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb  # scripts/chapter_1_introduction/README.md:7
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb  # scripts/chapter_1_introduction/README.md:9
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_1_introduction/tutorial_2_data.ipynb  # scripts/chapter_1_introduction/README.md:11
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_1_introduction/tutorial_3_fitting.ipynb  # scripts/chapter_1_introduction/README.md:13
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_1_introduction/tutorial_4_methods.ipynb  # scripts/chapter_1_introduction/README.md:15
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_1_introduction/tutorial_5_summary.ipynb  # scripts/chapter_1_introduction/README.md:17
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_1_non_linear_search.ipynb  # scripts/chapter_2_modeling/README.md:7
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_2_practicalities.ipynb  # scripts/chapter_2_modeling/README.md:9
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_3_realism_and_complexity.ipynb  # scripts/chapter_2_modeling/README.md:11
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_4_dealing_with_failure.ipynb  # scripts/chapter_2_modeling/README.md:13
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_5_linear_profiles.ipynb  # scripts/chapter_2_modeling/README.md:15
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_6_masking.ipynb  # scripts/chapter_2_modeling/README.md:17
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_7_results.ipynb  # scripts/chapter_2_modeling/README.md:19
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_2_modeling/tutorial_8_need_for_speed.ipynb  # scripts/chapter_2_modeling/README.md:21
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb  # scripts/chapter_3_search_chaining/README.md:8
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb  # scripts/chapter_3_search_chaining/README.md:10
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb  # scripts/chapter_3_search_chaining/README.md:12
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_3_search_chaining/tutorial_4_complex_source.ipynb  # scripts/chapter_3_search_chaining/README.md:16
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb  # scripts/chapter_3_search_chaining/README.md:14
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb  # scripts/chapter_3_search_chaining/README.md:18
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb  # scripts/chapter_4_pixelizations/README.md:7
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb  # scripts/chapter_4_pixelizations/README.md:9
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb  # scripts/chapter_4_pixelizations/README.md:11
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb  # scripts/chapter_4_pixelizations/README.md:13
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb  # scripts/chapter_4_pixelizations/README.md:15
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_6_modeling.ipynb  # scripts/chapter_4_pixelizations/README.md:17
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb  # scripts/chapter_4_pixelizations/README.md:19
-https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.14.2/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb  # scripts/chapter_4_pixelizations/README.md:21
-
 # GitHub refs (workspaces / removed tutorials)
 https://github.com/Jammy2211/PyAutoLogo/blob/main/gifs/pyautogalaxy.gif?raw=true  # README.md:7
 https://github.com/PyAutoLabs/autogalaxy_workspace/blob/main/scripts/chapter_1_introduction/HubbleTuningFork.jpg  # scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py:9

notebooks/chapter_1_introduction/README.md

@@ -4,14 +4,14 @@ In chapter 1, we introduce you to strong gravitational lensing and the core **Py
 
 # Files
 
-- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoGalaxy**'s visualization library.
+- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoGalaxy**'s visualization library.
 
-- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — How grids of (y,x) coordinates are used to create images of galaxies that ultimately quantify their morphology.
+- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — How grids of (y,x) coordinates are used to create images of galaxies that ultimately quantify their morphology.
 
-- [Tutorial 2: Data](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_2_data.ipynb) — Simulating and inspecting telescope imaging data of a galaxy, for example from the Hubble Space Telescope.
+- [Tutorial 2: Data](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_2_data.ipynb) — Simulating and inspecting telescope imaging data of a galaxy, for example from the Hubble Space Telescope.
 
-- [Tutorial 3: Fitting](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_3_fitting.ipynb) — How to fit imaging data of a galaxy and quantify whether a fit is good or bad.
+- [Tutorial 3: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_3_fitting.ipynb) — How to fit imaging data of a galaxy and quantify whether a fit is good or bad.
 
-- [Tutorial 4: Methods](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_4_methods.ipynb) — An overview of the different methods used to fit galaxies with.
+- [Tutorial 4: Methods](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_4_methods.ipynb) — An overview of the different methods used to fit galaxies with.
 
-- [Tutorial 5: Summary](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_5_summary.ipynb) — A summary of the chapter.
+- [Tutorial 5: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_5_summary.ipynb) — A summary of the chapter.

notebooks/chapter_2_modeling/README.md

@@ -4,18 +4,18 @@ In chapter 2, we'll take you through how to model galaxies using a non-linear se
 
 # Files
 
-- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a model and the concepts of a parameter space and priors.
+- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a model and the concepts of a parameter space and priors.
 
-- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk.
+- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk.
 
-- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a model.
+- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a model.
 
-- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoGalaxy finds an inaccurate model.
+- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoGalaxy finds an inaccurate model.
 
-- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters.
+- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters.
 
-- [Tutorial 6: Masking](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_6_masking.ipynb) — How to mask your data to improve the model.
+- [Tutorial 6: Masking](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_6_masking.ipynb) — How to mask your data to improve the model.
 
-- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a model.
+- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a model.
 
-- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time.
+- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_2_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time.

notebooks/chapter_3_search_chaining/README.md

@@ -5,14 +5,8 @@ different model.
 
 # Files
 
-- [Tutorial 1: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb) — Breaking the modeling procedure into a chained sequence of model-fits.
+- [Tutorial 1: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb) — Breaking the modeling procedure into a chained sequence of model-fits.
 
-- [Tutorial 2: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb) — How the results of earlier searches are passed to later searches.
+- [Tutorial 2: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb) — How the results of earlier searches are passed to later searches.
 
-- [Tutorial 3: Lens](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb) — Fitting the galaxy's light followed by its mass using chained searches.
-
-- [Tutorial 4: Two Lens galaxies](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb) — Modeling a galaxy with two lens galaxies using chained searches.
-
-- [Tutorial 5: Complex Source](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_4_complex_source.ipynb) — Using multiple light profiles to fit a complex and irregular source using chained searches.
-
-- [Tutorial 6: SLaM](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb) — Template pipelines for fitting model is standardized ways.
+- [Tutorial 3: x2 Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_3_x2_galaxies.ipynb) — Modeling two galaxies simultaneously using chained searches.

notebooks/chapter_4_pixelizations/README.md

@@ -4,18 +4,12 @@ In chapter 4, we use **Pixelizations** to reconstruct complex source galaxies on
 
 # Files
 
-- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane.
+- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane.
 
-- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels.
+- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels.
 
-- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb) — Inverting the mappings to reconstruct the source's light.
+- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb) — Inverting the mappings to reconstruct the source's light.
 
-- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework.
+- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework.
 
-- [Tutorial 5: Borders](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion.
-
-- [Tutorial 6: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_6_modeling.ipynb) — How to use inversions to fit a model.
-
-- [Tutorial 7: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb) — A Voronoi mesh which adapts to the mass model's magnification.
-
-- [Tutorial 8: Model Fit](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb) — An example modeling pipeline which uses an inversion.
+- [Tutorial 5: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_5_model_fit.ipynb) — An example modeling pipeline which uses an inversion.